Job Description

Summary

This role is pivotal in scaling our AI-driven Customer Service (CS) chat analysis. The specialist will manage data processing pipelines, optimize large language model (LLM) prompts, and collaborate closely with the existing project lead and cross-functional teams. The ultimate goal is to help expand classification coverage, drive bot adoption, and maintain high accuracy—all while ensuring faster delivery of new features and stakeholder requests.

Responsibilities:

  1. Work with data warehouse team, to maintain real time data pipeline of CS business domain, to ensure timely and high-quality data inputs to the AI models. 
  2. Design, implement, and refine LLM prompts for enhanced attribution analysis of CS conversations.
  3. Work closely with Ops teams to increase the stability of LLM solutions in a cloud or on-prem environment.
  4. Conduct A/B testing and iterative improvements on LLM performance, and maintaining result accuracy. 
  5. Develop and maintain back-end services and automation scripts using Java or Python, ensuring seamless integration with existing systems. 
  6. Troubleshoot performance bottlenecks, optimize code, and safeguard data security and privacy. 
  7. Collaborate with CS, BI, and SL teams to gather requirements, clarify feature demands, and communicate technical constraints. 
  8. Maintain clear, concise documentation of data work flows, LLM prompt templates, and best practices. 

Qualifications:

  1. Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
  2. 5+ years of hands-on experience in Java data processing and pipeline development.
  3. Experience with SQL/NoSQL databases, ETL pipelines, and data workflow orchestration tools (e.g., Airflow). 
  4. Proficient in Java / Python (at least one language) and Hive & Spark SQL programming languages.
  5. Hands-on experience with AWS, GCP, or Azure is a plus.
  6. Experience with LLM or NLP projects is highly desired
  7. Excellent communication and teamwork skills, with the ability to work in a cross-functional environment.
  8. Fluency in English is required to be able to coordinate with overseas partners and stakeholders. Additional languages would be an advantage.

Skills
  • AWS
  • Communications Skills
  • Development
  • Java
  • Python
  • Software Engineering
  • Team Collaboration
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